Category Archives: Machine Translation

Google Translate: Now in 51 languages

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In February of this year, Google Translate surpassed 40 languages.

Six months later, Google added ten more languages, a two-year growth trajectory illustrated below:

google_translate_languages

Google went from 13 languages to 51 languages in less than 16 months.

Not bad.

And, yes, I’m aware that we must not confuse quantity of translations with quality of translations. Your translation mileage will most certainly vary by language pair. Still, as language pairs go, Google is the only game in town across many.

Here are the 10 most recently added languages:

  • Albanian
  • Afrikaans
  • Belarusian
  • Icelandic
  • Irish
  • Macedonian
  • Malay
  • Swahili
  • Welsh
  • Yiddish

On a related noted, 41 of these languages are now incorporated into Google Docs.

Decyphering Google Translate on your web logs

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Whenever I read this site’s web logs, I’m always fascinated by the number of referrals via Google Translate.

Every month there seems to be more of them, which could mean that the quality of Google Translate is improving, or this site is doing better in the rankings, or some combination of the two. Or, it could be simply be that more people have discovered Google Translate.

Given my passion for country codes, it’s fair to say that I also enjoy language codes. And it is through language codes that you can figure out what languages users were translating your site “from” and “to.”

Here is one referral string from my site:

google_translate

First, you can see that the person was using Google Korea, so it’s fair to say the person was translating from English into Korean. The “To” line is actually the blog title post translated into Korean.

That was an easy one.

This next one is a bit more challenging:

google_translate2

This person was using Google.com, so you have to focus on the language codes. There are two here — an “id” (which follows  “hl=”) and an “en” (which follows “sl=”). What this means is the person was translating from English into Indonesian (Bahasa Indonesia).

Here is what the translated page looks like:

google_translate2a

The quick and easy way to know the target language is to focus on the “hl=” string. In the screen shot below, the target language is German.

google_translate3

And here is a language code reference if you want to study your web logs.

What I want to know is what percentage of web traffic is taken up by Google Translate. Anyone care to share their Web log stats?

Based on my cursory analysis, I would estimate the figure to be between 5% and 10%, but that’s very rough.

Bing Beats Google in Insta-translation

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Bing recently added a nifty new translation feature — one that is so simple and in many ways so obvious that I can’t help wondering why Google never got around to doing it. But that’s a topic for a later post.

For now, I’d like you to try entering the following text strings into both Bing and Google (to save you time I created pre-loaded hyperlinks):

Below are screen shots of the first text string in both Bing and Google. I’ll let the pictures speak for themselves:

bing-iloveyou

google_i_love_you

Google, despite its massively powerful translation engine, doesn’t simply answer your translation question. Instead, it provides links.

I realize that this is a relatively minor feature and that it currently only supports a small number of very common text strings, but it’s still a very handy feature for a translation geek such as myself.

Now, I’m not saying Bing is perfect. When it comes to technical searches — or when I just need to look up a Wikipedia article quickly — Google still does better, sometimes far better.

But I’m glad to see Bing integrating translation in an intuitive way. It’s a feature that I’ll be using again.

PS: Here is the blog announcement of this feature from Microsoft Translate team.

Why Pay for Translation if You Can Get it for Free?

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It was nice to wake up this morning and see this article in the New York Times about the emergence of machine translation and volunteer translation (aka crowdsourcing). These are two very important developments that every companies needs to be aware of — and possibly champion.

That said, I do wonder how this article is going to be received by the translators of the world who actually expect to be paid for their services.

For example the for-profit, invite-only conference company TED saved about $500,000 using volunteer translators. Clearly TED could have coughed up the money.

I can see this article spurring on CEOs across the land to think that they too can get free translations.

One thing I mentioned awhile back is that you need to be translation-worthy to get away with pro-bono services, particularly if you’re a for-profit company.

Facebook, Google and, now, TED appear to be translation-worthy. But I wouldn’t expect to see, say, General Motors succeeding in this area (though they could certainly use the help).

But the larger issue here is to the extent that volunteer translation for companies that can afford to pay for translation undermines the translation industry. I don’t believe machine translation undermines human translation because companies generally use it to translation text they would never have hired people to do (or they use it as a first pass before bringing on the human translators).

But volunteer translation is different.

Are  volunteer translators taking money away from their colleagues? After all, TED and Google and Facebook certainly can afford to pay. Or are volunteer translators raising awareness for the value of their work, thereby benefiting the translation industry as a whole?

Personally, I think we’re entering a dangerous area where companies that don’t know better are going to think they don’t have to pay for translation. This all reminds me of Seinfeld‘s George Costanza’s aversion to parking garages: Why should I pay, when if I apply myself, maybe I could get it for free?